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Extreme value modeling under power normalization

机译:功率归一化下的极值建模

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摘要

In this paper the mathematical modeling of extremes under power normalization is developed. An estimate of the shape parameter within the generalized extreme value distribution under power normalization is suggested. The statistical inference about the upper tail of a distribution function by using the power normalization is studied. Two models for generalized Pareto distribution under power normalization (GPDP) are given. Estimates for the shape and scale parameters within these GPDP's are obtained. Finally, a simulation study illustrates and corroborates theoretical results.
机译:在本文中,建立了功率归一化下的极限数学模型。建议对功率归一化下广义极值分布内的形状参数进行估计。利用幂归一化研究了关于分布函数上尾的统计推断。给出了功率归一化(GPDP)下广义帕累托分布的两种模型。获得了这些GPDP中形状和比例参数的估计值。最后,仿真研究说明并证实了理论结果。

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